https://doi.org/10.1140/epjs/s11734-025-01622-y
Regular Article
Hidden dynamics and FPGA-based hardware detection of memristive Rulkov neuron
School of Electrical and Automation Engineering, School of Computer Science and Technology, and School of Artificial Intelligence, Nanjing Normal University, 210023, Nanjing, China
Received:
25
January
2025
Accepted:
31
March
2025
Published online:
18
April
2025
Complex dynamical systems with hidden attractors exhibit extreme sensitivity to minor parameter variations and external perturbations. However, the hidden dynamics in discrete dynamical systems incorporating memristors have not been extensively studied. To accommodate this issue, this paper constructs a novel memristive Rulkov neuron (MRN) by integrating a classical Rulkov neuron with a discrete memristor autapse. First, the analysis of fixed points reveals that the MRN exhibits either infinitely many line fixed points or none, depending on the system parameter. Subsequently, bifurcation diagrams, Lyapunov exponents, phase diagrams, iterative sequences, and basins of attraction are utilized to investigate the underlying hidden dynamical behaviors. The numerical experiments demonstrate that the MRN shows hidden spiking discharge, mixed-mode discharge, hidden discharge regime transition, multistability, and antimonotonicity. Finally, an field programmable gate array (FPGA)-based hardware detection platform is developed, which supports real-time capture of hidden attractors and discharge waveforms.
Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
